The search for anomalies covers an almost unlimited
number of potential patterns. Some of them may be real, but many emerge
by chance alone

One of the most maligned ideas in economics is the efficient market
hypothesis, perhaps because what is actually a rather technical
statement about financial market returns is conflated with some entirely
different claim about the superiority of free markets over government
dirigisme.

The EMH has various forms, but in brief its message is very simple:
an individual investor cannot reliably outperform financial markets. The
reasoning is equally simple: money doesn’t get left around on the
pavement for very long. If it was obvious that the stock market would
rise tomorrow, investors would buy shares immediately and the stock
market would rise today instead. Anything that could reasonably be
anticipated already has been anticipated, and so markets instead respond
only to genuinely unexpected news.

But the EMH has a problem: researchers keep discovering predictable
patterns in the data, and such patterns amount to big piles of money
being left on the sidewalk.The most famous of these is probably the
“January effect”: that returns are particularly high in that month. The
January effect was originally explained by investors selling shares in
December for tax reasons, depressing prices. Whether or not this is
true, the EMH says that other investors should stand ready to buy those
cheap shares in December, and the January effect should simply not
exist.

The existence of the January effect and countless other anomalies
looks like a puzzle for the EMH. But it is really only a puzzle if the
anomalies suggest profitable trading strategies. That will not be true
if an apparent anomaly turns out to be pure coincidence. The search for
stock market anomalies covers thousands of stocks, tens of thousands of
daily returns, and an almost unlimited number of potential patterns to
be examined. Some patterns may be real, but many emerge by chance alone.

For instance, one recent discovery is that an asset’s monthly return
can be predicted by looking at the same asset’s maximum daily return
during the preceding month. Did you have to read that twice? It’s a
pretty obscure finding, and where there are so many such candidates to
be identified as an anomaly, some will be pure coincidence....MORE